Ultratiefe Pyrosequenz-Analyse (UDPS) von neu beschriebenen seltenen Resistenzvarianten der Hepatitis C Virus NS3 Protease bei Patienten, die mit Telaprevir oder Boceprevir behandelt wurden

Molecular characterization of hepatitis C virus for subtype determination and resistance-associated substitutions detection among Chinese voluntary blood donors

BACKGROUND

The high prevalence of hepatitis C virus (HCV) infection and the resulting burden of the disease are significant issues to public health worldwide. Although direct-acting antiviral drugs (DAAs) with good tolerance and bioavailability are available, resistance-associated substitutions (RASs) often jeopardize the successful sustainment of virological responses in HCV treatment. High-frequency baseline RASs in treatment-naïve patients can lead to failures in DAA treatment. Clinical data on HCV RASs in patients from China are limited and require investigations.

METHODS

262 HCV RNA positive plasma from Chinese blood donors were genotyped and amplified with subtype-specific primers for NS3 and NS5A regions. RASs were analyzed using Geno2pheno. The codon usage of each resistance-associated substitution was calculated for genetic barrier analysis.

RESULTS

The two main subtypes in mainland China were 1b and 2a, followed by subtype 6a, 3b, 3a, and 1a. In NS3 region of 1b subtype, substitutions (T54S, V55A, Y56F, Q80 K/L, S122 G/T, R117 H/C, V170I and S174A) were present in 89.7% (96/107) of the samples. Other RASs (M28L, R30Q, P58 L/S and Y93H) were observed in 22.1% (25/113) of the samples in NS5A region. A crucial RAS, Q80K, and two other mutations (S122G + V170I) was identified in the same sequence, which reduced its susceptibility to protease inhibitor ASV and resulted in resistance to SMV. In NS5A, Y93H was detected in 9.7% (11/113) of the 1b samples, leading to medium-to-high level resistance to all six commercialized NS5A inhibitors. S122G-NS3 and Y93H-NS5A occurred simultaneously in 38.1% (7/22) of the samples with mutations in both two regions. Moreover, codon usage of S122G-NS3 and Y93H-NS5A revealed that both variants had the lowest genetic barrier and required only one transition to confer resistance.

CONCLUSIONS

Low genetic barriers facilitated the generation of resistance mutants and threated the efficacy of DAA regimens. The baseline RASs posed a great challenge to real-world DAA application.

Exploring resistance pathways for first-generation NS3/4A protease inhibitors boceprevir and telaprevir using Bayesian network learning

Resistance-associated variants (RAVs) have been shown to influence treatment response to direct-acting antivirals (DAAs) and first generation NS3/4A protease inhibitors (PIs) in particular. Interpretation of hepatitis C virus (HCV) genotypic drug resistance remains a challenge, especially in patients who previously failed DAA therapy and need to be retreated with a second DAA based regimen. Bayesian network (BN) learning on HCV sequence data from patients treated with DAAs could provide insight in resistance pathways against PIs for HCV subtypes 1a and 1b, in a similar way as applied before for HIV. The publicly available 'Rega-BN' tool chain was developed to study associative analyses for various pathogens. Our first analysis, comparing sequences from PI-naïve and PI-experienced patients, determined that NS3 substitutions R155K and V36M arise with PI-exposure in HCV1a infected patients, and were defined as major and minor resistance-associated variants respectively. NS3 variant 174H was newly identified as potentially related to PI resistance. In a second analysis, NS3 sequences from PI-naïve patients who cleared the virus during PI therapy and from PI-naïve patients who failed PI therapy were compared, showing that NS3 baseline variant 67S predisposes to treatment-failure and variant 72I to treatment success. This approach has the potential to better characterize the role of more RAVs, if sufficient therapy annotated sequence data becomes available in curated public databases. In addition, polymorphisms present in baseline sequences that predispose patients to therapy failure can be identified using this approach.

Geno2pheno[HCV] - A Web-based Interpretation System to Support Hepatitis C Treatment Decisions in the Era of Direct-Acting Antiviral Agents. PLoS One. 2016;11:e0155869. [PMID: 27196673 PMCID: PMC4873220 DOI: 10.1371/journal.pone.0155869]

The face of hepatitis C virus (HCV) therapy is changing dramatically. Direct-acting antiviral agents (DAAs) specifically targeting HCV proteins have been developed and entered clinical practice in 2011. However, despite high sustained viral response (SVR) rates of more than 90%, a fraction of patients do not eliminate the virus and in these cases treatment failure has been associated with the selection of drug resistance mutations (RAMs). RAMs may be prevalent prior to the start of treatment, or can be selected under therapy, and furthermore they can persist after cessation of treatment. Additionally, certain DAAs have been approved only for distinct HCV genotypes and may even have subtype specificity. Thus, sequence analysis before start of therapy is instrumental for managing DAA-based treatment strategies. We have created the interpretation system geno2pheno_[HCV] (g2p_[HCV]) to analyse HCV sequence data with respect to viral subtype and to predict drug resistance. Extensive reviewing and weighting of literature related to HCV drug resistance was performed to create a comprehensive list of drug resistance rules for inhibitors of the HCV protease in non-structural protein 3 (NS3-protease: Boceprevir, Paritaprevir, Simeprevir, Asunaprevir, Grazoprevir and Telaprevir), the NS5A replicase factor (Daclatasvir, Ledipasvir, Elbasvir and Ombitasvir), and the NS5B RNA-dependent RNA polymerase (Dasabuvir and Sofosbuvir). Upon submission of up to eight sequences, g2p_[HCV] aligns the input sequences, identifies the genomic region(s), predicts the HCV geno- and subtypes, and generates for each DAA a drug resistance prediction report. g2p_[HCV] offers easy-to-use and fast subtype and resistance analysis of HCV sequences, is continuously updated and freely accessible under http://hcv.geno2pheno.org/index.php. The system was partially validated with respect to the NS3-protease inhibitors Boceprevir, Telaprevir and Simeprevir by using data generated with recombinant, phenotypic cell culture assays obtained from patients’ virus variants.